class_docstr: Generic PyTorch-Lightning class that must be initialized with a PyTorch module.
class_docstr_tok: ["Generic","PyTorch-Lightning","class","that","must","be","initialized","with","a","PyTorch","module","."]
code: def add_to_argparse(parser):
      parser.add_argument(
          "--optimizer",
          type=str,
          default=OPTIMIZER,
          help="optimizer class from torch.optim",
      )
      parser.add_argument("--lr", type=float, default=LR)
      parser.add_argument("--weight_decay", type=float, default=0.01)
      return parser
  
file_path: DeepKE/src/deepke/relation_extraction/few_shot/lit_models/base.py
imports: import torch
  from transformers.optimization import get_linear_schedule_with_warmup
  from torch import nn
label_desc: Use image node_id 2 for calling the BaseLitModel obj's underlying member method code with example usage: obj.add_to_argparse(parser) and returns: parser